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Updated: Jun 15, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
Sensitivity analysis of informatively coarsened data using pattern mixture models
Michelle Shardell1, Samer S El-Kamary
1Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Abstract:
We use the framework of coarsened data to motivate performing sensitivity analysis in the presence of incomplete data. To perform the sensitivity analysis, we specify pattern-mixture models to allow departures from the assumption of coarsening at random, a generalization of missing at random and independent censoring. We apply the concept of coarsening to address potential bias from missing data and interval-censored data in a randomized controlled trial of an herbal treatment for acute hepatitis. Computer code using SAS PROC NLMIXED for fitting the models is provided.
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